keptn VS kubernetes

One of the other places I spent a lot of time at at KubeCon NA was the CNCF Project Pavillion. I was very happy to see that it was a bit larger than the area we had during KubeCon EU, but I still wish that it was bigger and wasn’t so tucked away in the corner. A number of booths were showcasing their projects with demos through the week, hosted Q&A time, and gave away swag. If you are still trying to understand the Cloud Native Ecosystem, you can look at this very extensive map of the landscape and projects under the CNCF, some of which are more advanced than others. Of course I’m biased, but I’m really excited for the work that Keptn is doing in helping developers have more control over their application lifecycle. I’m also very excited to see where Backstage goes and how other CNCF projects can integrate with their service catalog.

I can’t speak from experience, but I think Keptn might be worth looking into: https://keptn.sh/

Go try this out and share your feedback on what you like about this integration and what you’d like improved. Feel free to create issues, engage in discussions on the Keptn Slack and Litmus Github repository. Stay tuned for more updates on how you can leverage Keptn & LitmusChaos CNCF projects to build and ship resilient cloud-native applications!

If you want, you can also manually download the binary file from Github and install the CLI by moving it into your path.

In the field of software development, efficiency and agility are always sought after. In the era of cloud-native apps, traditional deployment techniques—which are frequently laborious and prone to errors—are starting to become obstacles. This is when Kubernetes and GitOps come in handy.

Are you looking for a hassle-free way to deploy Moodle™ Learning Management Systems (LMS) on Kubernetes? Look no further! Krestomatio presents the LMS Moodle Operator, an open-source Kubernetes Operator designed to simplify the deployment and management of Moodle instances on Kubernetes clusters. Let's dive into what makes this tool a great choice for Moodle administrators and developers alike.

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Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.

To learn more, you can start by exploring the official Kubernetes documentation.

With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.

This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.

We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.

"You are holding it wrong", huh?

From the homepage https://kubernetes.io/:

"Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications."

Do you see "not recommended for smaller-scale applications" anywhere? Including on the entire home page? Looking for "small", "big" and "large" also yields nothing.